CN111383115A - Transaction place abnormal behavior monitoring and analyzing method and system - Google Patents
Transaction place abnormal behavior monitoring and analyzing method and system Download PDFInfo
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Abstract
The invention provides a method for monitoring and analyzing abnormal behaviors of trading places, which comprises the following steps: collecting data of a trading place platform; setting a risk index system; judging risk items and calculating weight; and calculating a risk score according to a risk model formula, and dividing the risk grade of the platform. The invention further provides a transaction place abnormal behavior monitoring and analyzing system. The business transaction monitoring, the business and business judicial administration monitoring, the Internet public opinion monitoring, the user scale monitoring and the network medium compliance monitoring of the trading places are combined to realize the multidimensional comprehensive analysis and judgment, and finally the risk index system setting of the trading places is realized through the risk item judgment and the risk model formula setting calculation, so that the illegal behaviors of the trading places are efficiently monitored.
Description
Technical Field
The invention relates to the field of financial risk analysis, in particular to a method and a system for monitoring and analyzing abnormal behaviors in a trading place.
Background
In China, trading places play a remarkable role in activating financial markets, promoting the liquidity of financial assets and the like. The local government sets some places for conducting equity and commodity trading successively according to the needs of developing economy, wherein the financial asset trading places are used as beneficial supplements of a multi-level capital market system, thereby widening the financing channel of small and medium-sized enterprises and injecting a source of running water for the benign development of local economy. However, while taking positive effect, trading places also expose some risks and problems, such as illegal securities futures business development, split open issue of suspected equity, centralized trading for suspected violations, illegal release of investment income products, and illegal transfer of bad assets.
Therefore, there is a need in the art for a transaction location abnormal behavior monitoring and analyzing method and system.
Accordingly, the present invention is directed to such a system.
Disclosure of Invention
The invention aims to provide a transaction place abnormal behavior monitoring and analyzing method and system to solve at least one technical problem.
The invention provides a method for monitoring and analyzing abnormal behaviors of trading places, which comprises the following steps:
collecting data of a trading place platform;
setting a risk index system;
judging risk items and calculating weight;
and calculating a risk score according to a risk model formula, and dividing the risk grade of the platform.
By adopting the scheme, the data of the trading place platform can be comprehensively collected, the related data can be monitored, multi-dimensional comprehensive judgment is realized, and the risk index system and the risk model formula are utilized to realize the numeralization of the risk, so that the trading place platform is divided into the platform risk levels, and the illegal behaviors of the trading places can be efficiently monitored.
Further, the data of the trading place platform includes: business data, industrial and commercial data, judicial data, public opinion data, user data and network medium data.
By adopting the scheme, abnormal behaviors are monitored in the trading places through a plurality of data channels, and financial risks are prevented.
Further, the risk index system comprises at least two risk item levels, the risk item levels comprise at least one primary index type, and the primary index types of the same risk item level adopt the same weight calculation method.
By adopting the scheme, different calculation methods can be adopted for the primary index types of different risk levels, so that the primary index types of different risk levels have different calculation sensitivities, the calculation is simplified, and the efficiency is improved.
Further, the primary index type comprises at least one secondary index type, the secondary index type comprises at least one risk item, and the primary index type or the secondary index type is provided with a weight.
By adopting the scheme, the first-level index type is provided with the weight, so that condition judgment is facilitated, the calculation sensitivity is increased, the calculation process is simplified, and the efficiency is improved; the secondary index type is provided with the weight, so that the primary index type can be graded to obtain the weight conveniently, the calculation fineness is increased, and the fineness is improved.
Further, the method for calculating the weight comprises the following steps:
judging whether the secondary index type is provided with weight: if yes, the secondary index type obtains the weight as long as one of the risk items of the secondary index type meets the condition, and the weight obtained by the primary index type is the sum of the weights obtained by the secondary index types below the primary index type; if not, the first-level index type obtains the weight as long as one of the risk items in the first-level index type meets the condition.
By adopting the scheme, if the primary index type is provided with the weight, the primary index type has corresponding risk as long as one risk item meets the condition, and all risk items meet the condition and are also the corresponding weight, so that the evaluation is not repeated under the primary index type, the calculation process is simplified, and the sensitivity of the primary index type on the influence of the platform risk score is improved; if the secondary index types are provided with weights, the relevance between the secondary index types is not strong, different evaluation aspects of the primary index types are respectively described, the weight calculation of each secondary index type is not influenced mutually, the primary index types can obtain different weights according to different calculation results according to actual data, so that the platform risk value is influenced in a grading mode, the fineness is improved, the weights of the secondary index types are evaluated from multiple angles, and if one of the weights meets the condition, a corresponding risk exists, so that the evaluation is not repeated under the secondary index type, and the risk grade division is influenced.
Further, the risk model formula is:
wherein R represents the risk score of each trading place platform, n is the number of the first-level index types, and WiSetting weights for the class of primary indicators, SiWeights are calculated for the primary index types.
By adopting the scheme, the calculation of the risk score not only considers the weight value calculated according to the actual condition, but also sets the threshold value for the calculated weight value, and different threshold values are set for different first-level index types, so that the situation that the first-level index types occupy excessive scores, influence the proportion of the first-level index types occupying the risk score, and lose the influence effect of different risk item grades is prevented.
In another aspect, the present invention provides a system for monitoring and analyzing abnormal behavior of a transaction location, including:
the acquisition module is used for acquiring data of the trading place platform;
the setting module is used for setting a risk index system;
the judgment calculation module is used for judging the risk items and calculating the weight;
and the score dividing module is used for calculating a risk score according to a risk model formula and dividing the platform risk level.
By adopting the scheme, the data of the trading place platform can be comprehensively collected, the related data can be monitored, multi-dimensional comprehensive judgment is realized, and the risk index system and the risk model formula are utilized to realize the numeralization of the risk, so that the trading place platform is divided into the platform risk levels, and the illegal behaviors of the trading places can be efficiently monitored.
Further, the acquisition module comprises: the system comprises a service data unit, a business data unit, a judicial data unit, a public opinion data unit, a user data unit and a network media data unit.
By adopting the scheme, abnormal behaviors are monitored in the trading places through a plurality of data channels, and financial risks are prevented.
Further, the setting module includes:
a risk item grade setting unit for setting risk item grades of different grades and setting weight positions;
the first-level index type setting unit is used for setting different first-level index types, distributing risk item grades and judging whether to set weight according to the weight position;
the second-level index type setting unit is used for setting different second-level index types, distributing the first-level index types to which the second-level index types belong, and judging whether to set the weight according to the weight position;
and the risk item setting unit is used for setting different risk items and distributing the secondary index types.
By adopting the scheme, the weight position refers to whether the first-level index type or the second-level index type sets the weight, the risk item grade, the first-level index type, the second-level index type and the risk item are graded and set through the setting module, the management and the weight distribution of the risk item are convenient, different calculation methods can be adopted for the first-level index types of different risk grades, the first-level index types of different risk grades have different calculation sensitivities, the calculation is simplified, and the efficiency is improved.
Further, the determined calculation module includes:
a risk item determination unit for determining whether the risk item satisfies a condition;
and the weight calculation unit is used for calculating the calculation weight of each primary index type.
Further, the score partitioning module comprises:
the score calculating unit is used for calculating a risk score according to a risk model formula;
and the grade division unit is used for dividing the platform risk grade.
In conclusion, the invention has the following beneficial effects:
1. the business transaction monitoring, the business and judicial administration monitoring, the Internet public opinion monitoring, the user scale monitoring and the network medium compliance monitoring of the trading places are combined to realize the multidimensional comprehensive analysis and judgment, and finally the risk index system setting of the trading places is realized through the risk item judgment and the risk model formula setting calculation, so that the illegal behaviors of the trading places are efficiently monitored;
2. different calculation methods can be adopted for the primary index types of different risk levels, so that the primary index types of different risk levels have different calculation sensitivities, the calculation is simplified, and the efficiency is improved;
3. the first-level index type is provided with weight, so that condition judgment is facilitated, the calculation sensitivity is increased, the calculation process is simplified, and the efficiency is improved; the secondary index type is provided with the weight, so that the primary index type can be graded to obtain the weight conveniently, the calculation fineness is increased, and the fineness is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of an embodiment of a transaction location abnormal behavior monitoring and analyzing method according to the present invention;
FIG. 2 is a schematic diagram of another embodiment of a transaction location abnormal behavior monitoring and analyzing method according to the present invention;
FIG. 3 is a schematic diagram of an embodiment of an abnormal behavior monitoring and analyzing system of a transaction location according to the present invention;
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
The terms mentioned in the invention are to be interpreted:
(1) service data: the platform transaction mode, the issuing sale condition and the external cooperation condition declared in a transaction mode module or a transaction rule module in a website navigation bar of a transaction place are referred to.
(2) And (3) industrial and commercial data: the method refers to that the affiliated company declared by a trading place platform officer obtains information such as suspected industrial and commercial risks, judicial risks, operational risks and the like of an operation main body through interfaces such as 'skyhook inspection' and 'enterprise inspection'.
(3) Public opinion data: it refers to whether the trading place platform is suspected of important negative public sentiment in each news media propagation channel (such as high-speed running, fraud, group event, illegal self-thawing, illegal operation, illegal propaganda [ public propaganda ]).
(4) Network media data: the method comprises the steps of referring to a website, APP and WeChat public account information of a trading place platform, and monitoring whether the APP and the WeChat public account are abnormal or not by acquiring website access conditions, website announcements, website access amount, whether a server is overseas or not, whether an ICP records the number or not and the like in the website.
(5) Judicial data: the information refers to specific judicial conditions, such as status and times of main body of legal litigation, information of the deceased person, information of the executed person or information of judicial assistance, such as equity freezing, and the like.
(6) User data: the scale abnormal change condition of the users of the trading place platform is indicated, such as the proportion of newly added users, the proportion of users in each region, the fluctuation of the users of newly added men and women and the age group, and the like.
The present invention will be described in detail below by way of examples.
Example one
Referring to fig. 1, the present embodiment provides a transaction location abnormal behavior monitoring and analyzing method, including the following steps:
s101, collecting data of a trading place platform;
s102, setting a risk index system;
s103, judging risk items and calculating weight;
and S104, calculating a risk value according to a risk model formula, and dividing the risk level of the platform.
By adopting the scheme, the data of the trading place platform can be comprehensively collected, the related data can be monitored, multi-dimensional comprehensive judgment is realized, and the risk index system and the risk model formula are utilized to realize the numeralization of the risk, so that the trading place platform is divided into the platform risk levels, and the illegal behaviors of the trading places can be efficiently monitored.
In a preferred embodiment of the present invention, the data of the trading place platform includes: business data, industrial and commercial data, judicial data, public opinion data, user data and network medium data.
By adopting the scheme, abnormal behaviors are monitored in the trading places through a plurality of data channels, and financial risks are prevented.
In a preferred embodiment of the present invention, the risk indicator system includes at least two risk item levels, the risk item level includes at least one primary indicator type, and the primary indicator types of the same risk item level adopt the same weight calculation method.
By adopting the scheme, different calculation methods can be adopted for the primary index types of different risk levels, so that the primary index types of different risk levels have different calculation sensitivities, the calculation is simplified, and the efficiency is improved.
In a preferred embodiment of the present invention, the primary index type includes at least one secondary index type, the secondary index type includes at least one risk item, and the primary index type or the secondary index type is provided with a weight.
By adopting the scheme, the first-level index type is provided with the weight, so that condition judgment is facilitated, the calculation sensitivity is increased, the calculation process is simplified, and the efficiency is improved; the secondary index type is provided with the weight, so that the primary index type can be graded to obtain the weight conveniently, the calculation fineness is increased, and the fineness is improved.
In the specific implementation process, the risk item grade, the primary index type, the secondary index type, the risk item and the corresponding weight are set according to the risk index system of the trading place in the table 1.
TABLE 1 trading floor Risk indicator System
Referring to fig. 2, in a preferred embodiment of the present invention, the method of calculating the weight includes the steps of: s310, judging whether the secondary index type is provided with a weight: if yes, S311, if the risk item of the secondary index type meets a condition, the secondary index type obtains the weight, and the weight obtained by the primary index type is the sum of the weights obtained by the secondary index types below the secondary index type; if not, S312, the first-level index type obtains the weight as long as one risk item in the first-level index type meets the condition.
In the specific implementation process, if the primary index type is 'platform basic plane', the weight setting position is in the secondary level for the medium risk, and the risk items meet the following conditions: "no relevant government records", "no business information", "platform operation subject suffering administrative penalty", will obtain 20% weight of "business risk" and 5% weight of "operation risk" in the secondary index type, then the primary index type "platform fundamental plane" obtains (20+ 5)% weight; if the first-level index type ' platform service ' is high-risk, the weight position is in the first level, and if only one risk item is satisfied, if the platform adopts ' anonymous trading ' trading mode to trade ', the first-level index type ' platform service ' obtains 50% weight.
By adopting the scheme, if the primary index type is provided with the weight, the corresponding risk exists as long as one risk item of the primary index type meets the condition, and all risk items meet the corresponding weight, so that the evaluation is not repeated under the primary index type, the calculation process is simplified, and the sensitivity of the influence of the primary index type on the platform risk score is improved; if the second-level index types are provided with weights, the relevance between the second-level index types is not strong, different aspects of the first-level index types are respectively described, the weight calculation of each second-level index type is not influenced mutually, the first-level index types can obtain different weights according to different calculation results so as to influence the platform risk value in a grading mode and improve the fineness, the weights of the second-level index types are evaluated from multiple angles, and if one of the weights meets the condition, a corresponding risk exists, so that the evaluation is not repeated under the second-level index types, and the division of the risk grade is influenced.
In a preferred embodiment of the present invention, the risk model formula is:
whereinR represents the risk score of each trading place platform, n is the number of the first-level index types, and WiSetting weights for the class of primary indicators, SiWeights are calculated for the primary index types.
In the specific implementation process, the set weight of the platform service is 50%, the set weight of the platform basic surface is 30%, the set weight of the platform scale is 5%, the set weight of the platform medium is 15%, and the corresponding calculation weights are respectively: "platform traffic" is 50%, "platform base" is 35%, "platform scale" is 2%, "platform medium" is 2%, and the corresponding risk score is 50% + 30% + 2% + 84%.
By adopting the scheme, the calculation of the risk score not only considers the weight value calculated according to the actual condition, but also sets the threshold value for the calculated weight value, and different threshold values are set for different first-level index types, so that the situation that the first-level index types occupy excessive scores, influence the proportion of the first-level index types occupying the risk score, and lose the influence effect of different risk item grades is prevented.
The method for dividing the platform risk level comprises the step of judging the platform risk level according to the risk value range of the risk value.
In the specific implementation process, the classification of the risk platform grades of the trading places is carried out according to the table 2, and different warning measures such as message reminding, mail sending and the like can be adopted according to different platform risk grades to inform related personnel.
TABLE 2 trading floor Risk platform level settings
| Serial number | Range of risk values | Platform risk rating |
| 1 | 50～100 | High risk |
| 2 | 15～49 | Middle risk |
| 3 | 1～14 | Low risk |
| 4 | 0 | Without risk |
Example two
Referring to fig. 3, the present embodiment provides a system for monitoring and analyzing abnormal behavior of a trading place, including:
the acquisition module is used for acquiring data of the trading place platform;
the setting module is used for setting a risk index system;
the judgment calculation module is used for judging the risk items and calculating the weight;
and the score dividing module is used for calculating a risk score according to a risk model formula and dividing the platform risk level.
By adopting the scheme, the data of the trading place platform can be comprehensively collected, the related data can be monitored, multi-dimensional comprehensive judgment is realized, and the risk index system and the risk model formula are utilized to realize the numeralization of the risk, so that the trading place platform is divided into the platform risk levels, and the illegal behaviors of the trading places can be efficiently monitored.
In a preferred embodiment of the present invention, the acquisition module includes: the system comprises a service data unit, a business data unit, a judicial data unit, a public opinion data unit, a user data unit and a network media data unit.
By adopting the scheme, abnormal behaviors are monitored in the trading places through a plurality of data channels, and financial risks are prevented.
In a preferred embodiment of the present invention, the setting module includes:
a risk item grade setting unit for setting risk item grades of different grades and setting weight positions;
the first-level index type setting unit is used for setting different first-level index types, distributing risk item grades and judging whether to set weight according to the weight position;
the second-level index type setting unit is used for setting different second-level index types, distributing the first-level index types to which the second-level index types belong, and judging whether to set the weight according to the weight position;
and the risk item setting unit is used for setting different risk items and distributing the secondary index types.
By adopting the scheme, the weight position refers to whether the first-level index type or the second-level index type sets the weight, the risk item grade, the first-level index type, the second-level index type and the risk item are graded and set through the setting module, the management and the weight distribution of the risk item are convenient, different calculation methods can be adopted for the first-level index types of different risk grades, the first-level index types of different risk grades have different calculation sensitivities, the calculation is simplified, and the efficiency is improved.
In a preferred embodiment of the present invention, the determination calculation module includes:
a risk item determination unit for determining whether the risk item satisfies a condition;
and the weight calculation unit is used for calculating the calculation weight of each primary index type.
Further, the score partitioning module comprises:
the score calculating unit is used for calculating a risk score according to a risk model formula;
and the grade division unit is used for dividing the platform risk grade.
It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the protection scope of the claims of the present invention.
Claims (10)
1. A transaction place abnormal behavior monitoring and analyzing method is characterized by comprising the following steps: the method comprises the following steps:
collecting data of a trading place platform;
setting a risk index system;
judging risk items and calculating weight;
and calculating a risk score according to a risk model formula, and dividing the risk grade of the platform.
2. The transaction location abnormal behavior monitoring and analyzing method according to claim 1, wherein: the data for the trading floor platform includes: business data, industrial and commercial data, judicial data, public opinion data, user data and network medium data.
3. The transaction location abnormal behavior monitoring and analyzing method according to claim 1 or 2, wherein: the risk index system comprises at least two risk item levels, the risk item levels comprise at least one primary index type, and the primary index types of the same risk item level adopt the same weight calculation method.
4. The transaction location abnormal behavior monitoring and analyzing method according to claim 3, wherein: the first-level index type comprises at least one second-level index type, the second-level index type comprises at least one risk item, and the first-level index type or the second-level index type is provided with weight.
5. The transaction location abnormal behavior monitoring and analyzing method according to claim 4, wherein: the method for calculating the weight comprises the following steps:
judging whether the secondary index type is provided with weight: if yes, the secondary index type obtains the weight as long as one of the risk items of the secondary index type meets the condition, and the weight obtained by the primary index type is the sum of the weights obtained by the secondary index types below the primary index type; if not, the first-level index type obtains the weight as long as one of the risk items in the first-level index type meets the condition.
6. A transaction place abnormal behavior monitoring and analyzing system is characterized in that: the method comprises the following steps:
the acquisition module is used for acquiring data of the trading place platform;
the setting module is used for setting a risk index system;
the judgment calculation module is used for judging the risk items and calculating the weight;
and the score dividing module is used for calculating a risk score according to a risk model formula and dividing the platform risk level.
7. The system for monitoring and analyzing abnormal behavior of trading places according to claim 6, wherein: the acquisition module comprises: the system comprises a service data unit, a business data unit, a judicial data unit, a public opinion data unit, a user data unit and a network media data unit.
8. The system for monitoring and analyzing abnormal behavior of trading places according to claim 6 or 7, wherein: the setting module includes:
a risk item grade setting unit for setting risk item grades of different grades and setting weight positions;
the first-level index type setting unit is used for setting different first-level index types, distributing the risk item grades and judging whether to set the weight according to the weight position;
the second-level index type setting unit is used for setting different second-level index types, distributing the first-level index types to which the second-level index types belong, and judging whether to set the weight according to the weight position;
and the risk item setting unit is used for setting different risk items and distributing the secondary index types.
9. The system for monitoring and analyzing abnormal behavior of trading places according to claim 8, wherein: the determined calculation module includes:
a risk item determination unit for determining whether the risk item satisfies a condition;
and the weight calculation unit is used for calculating the calculation weight of each primary index type.
10. The system for monitoring and analyzing abnormal behavior of trading places according to claim 9, wherein: the score partitioning module comprises:
the score calculating unit is used for calculating a risk score according to a risk model formula;
and the grade division unit is used for dividing the platform risk grade.
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| CN111967802A (en) * | 2020-09-25 | 2020-11-20 | 杭州安恒信息安全技术有限公司 | Enterprise financial risk quantitative analysis and early warning method, device and equipment |
| CN112631887A (en) * | 2020-12-25 | 2021-04-09 | 百度在线网络技术（北京）有限公司 | Abnormality detection method, abnormality detection device, electronic apparatus, and computer-readable storage medium |
| CN113763160A (en) * | 2021-01-20 | 2021-12-07 | 国家计算机网络与信息安全管理中心 | Illegal transaction mode identification, judgment and tracking method for transaction places |
| CN116187936A (en) * | 2023-02-03 | 2023-05-30 | 上海麦德通软件技术有限公司 | Work order intelligent generation system based on cloud platform |
| CN116260533A (en) * | 2023-05-15 | 2023-06-13 | 成都国营锦江机器厂 | Intelligent anti-interference ultrashort wave radio station test platform and application method |
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